Sickle cell disease is an autosomal recessive disorder and the most common monogenic genetic disease in the United States. Mortality in sickle cell patients with elevated pulmonary pressures is believed to be significantly higher when compared to those with normal pulmonary pressures. We have enrolled 659 subjects and 103 controls in a study of the prevalence and prognosis of subjects with sickle cell disease and suspected pulmonary hypertension. All subjects were screened with transthoracic echocardiograms and the tricuspid regurgitant jet velocity (TRV) used to estimate the pulmonary artery systolic pressure. Additional phenotypic information related to the manifestations of sickle cell disease is also collected at evaluation. Suspected pulmonary hypertension was prospectively defined by a TRV >= 2.5 m/sec and severe pulmonary hypertension defined by a TRV >= 3.0 m/sec. Subjects have been followed for a mean of 6 years and censored at time of death or loss to follow-up. There have been 72 new subjects enrolled at the NIH during this year; 16 were controls and 56 were subjects with sickle cell disease. There were no new subjects enrolled at the Howard University site. Total enrolled at Howard University is 131 and the total enrolled at NIH is 696. Total enrollment for all sites is 827. Subject enrollment is ongoing. We are conducting 2, 4, 6, 8 and 10 year follow-up visits for comprehensive data collection. We also completed comprehensive survival update on all subjects enrolled to date. All new subjects had corresponding biospecimens collected for genomic investigations. Our goal is to recruit at least 1000 subjects with sickle cell disease for initial exploratory genetic studies. This will allow for sufficient statistical power to preliminarily identify genetic modifiers. Variants in the GCH1 gene, which have previously been identified as modulators of pain in other diseases, are associated with increased risk of severe vaso-occlusive pain crises in a case control study. GCH1 is the rate limiting step for the synthesis of BH4 (tetrahydrobiopterin) which is an essential co-factor for the synthesis of nitric oxide, catecholamines, serotonin, and phenylalanine metabolism. In vitro, this GCH1 haplotype is associated with increased gene expression. We believe that this result indicates that this is a unique African haplotype associated with increased BH4 and increased pain. Surprisingly, this haplotype is not associated with pulmonary hypertension in SCD despite the biological suggestion that the African haplotype might promote nitric oxide production. Variants in the MYH9 gene are associated with decreased glomerular filtration rate in SCD. Genetic markers in the region of MYH9 on chromosome 22 have been identified as major risk factors for focal segmental glomerular sclerosis (FSGS) in African American populations. This association study extends this work to a disease specific patient population that is at high risk for renal insufficiency. A genome wide association study several phenotypes in sickle cell anemia is in progress using ancestry informative markers that were identified from the HapMap project. Initially, we will analyze pain as a phenotype. The phenotype defining cases in this study is >1 severe pain crisis per year which provides >80% statistical power to detect genome wide associations with a relative risk of 2 or higher. Studies are also underway to also determine if gene expression profiling can also be used to identify sub-phenotypes of sickle cell disease. In a pilot study, we have isolated RNA from different peripheral blood preparations to determine which is the most informative for larger studies. For this pilot, subjects with SS sickle cell disease were compared to those with SC sickle cell disease because they each have distinct clinical manifestations. Preliminary analysis suggests that SS and SC have nearly identical gene expression profiles despite their clinical differences. In a larger follow-up study, we compared gene expression profiles for 2 sickle cell anemia sub-phenotypes defined by a plasma biomarker using exon arrays. These data sets are presently undergoing detailed analysis.